{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. Setting specifications"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "global graph_opts title(, justification(left) color(black) span pos(11)) graphregion(color(white)) ylab(,angle(0) nogrid) xtit(,placement(left) justification(left)) yscale(noline) xscale(noline) legend(region(lc(none) fc(none)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. Uploading data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "use \"https://github.com/SaoriIwa/Stata-IE-Visual-Library/raw/master/Library/Charts/Chart%20of%20comparison%20of%20marginal%20effects%20from%20different%20models/data.dta\", clear"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. Creating the graph with regression results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "cap mat drop theResults\n",
    "\tlocal theLabels \"\"\n",
    "\tlocal x = 15.5\n",
    "\n",
    "\tqui foreach var of varlist ??_correct refer med_any med_class_any_6 med_class_any_16 {\n",
    "\n",
    "\t\tlocal theLabel : var label `var'\n",
    "\t\tlocal theLabels `\"`theLabels' `x' \"`theLabel'\"\"'\n",
    "\t\tlocal x = `x' - 2\n",
    "\t\n",
    "\t\treg `var' facility_private i.case_code \n",
    "\t\t\n",
    "\t\tmat a = r(table)\n",
    "\t\t\tlocal b = a[1,1]\n",
    "\t\t\tlocal ll = a[5,1]\n",
    "\t\t\tlocal ul = a[6,1]\n",
    "\t\t\tmat a = [`b',`ll',`ul',1]\n",
    "\t\t\t\n",
    "\t\t\tmat rownames a = \"`var'\"\n",
    "\t\t\n",
    "\t\tlogit `var' facility_private i.case_code \n",
    "\t\t\tmargins , dydx(facility_private)\n",
    "\t\t\n",
    "\t\tmat b = r(table)\n",
    "\t\t\tlocal b = b[1,1]\n",
    "\t\t\tlocal ll = b[5,1]\n",
    "\t\t\tlocal ul = b[6,1]\n",
    "\t\t\tmat b = [`b',`ll',`ul',2]\n",
    "\t\t\t\n",
    "\t\t\tmat rownames b = \"`var'\"\n",
    "\t\t\t\n",
    "\t\tmat theResults = nullmat(theResults) \\ a \\ b \n",
    "\t\t\n",
    "\t\t}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "This front-end cannot display the desired image type."
      ]
     },
     "metadata": {
      "image/png": {
       "height": 436,
       "width": 600
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "mat colnames theResults = \"b\" \"ll\" \"ul\" \"type\"\n",
    "qui matlist theResults\n",
    "\n",
    "\tclear\n",
    "qui svmat theResults , names(col)\n",
    "\t\n",
    "qui gen n = _n\n",
    "qui replace n = 17-n\n",
    "\n",
    "\ttw ///\n",
    "\t\t(rcap ll ul n if type == 1 , hor lc(navy)) ///\n",
    "\t\t(scatter n b if type == 1 , mc(black)) ///\n",
    "\t\t(rcap ll ul n if type == 2 , hor lc(maroon)) ///\n",
    "\t\t(scatter n b if type == 2 , mc(black)) ///\n",
    "\t\t, $graph_opts ylab(`theLabels') ytit(\" \") xlab(-1 \"-100p.p.\" -.5 `\"\"-50p.p.\" \"{&larr} Favors Public\"\"' 0 \"No Effect\" .5 `\"\"+50p.p.\" \"Favors Private {&rarr}\"\"' 1 \"+100p.p.\") ///\n",
    "\t\t\txline(0 , lc(gs12) lp(dash)) legend(order(2 \"Marginal Effect\" 1 \"Linear Model\" 3 \"Logistic Model\") r(1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. Exporting the graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "qui graph export \"figure.png\" , replace width(2000)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Stata",
   "language": "stata",
   "name": "stata"
  },
  "language_info": {
   "file_extension": ".do",
   "mimetype": "text/x-stata",
   "name": "stata"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
